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Previous research has shown that elevating fuel injection pressure results in better air-fuel mixture formation, allowing for a further increase in maximum exhaust gas recirculation (EGR) rate while consequently reducing NOx emissions. The aim of this paper is to find out whether there is an optimum injection pressure for lowest soot-NOx emissions at a given boost pressure in high-speed diesel engines. Experiments are carried out on a single-cylinder research engine with a prototype common-rail system, capable of more than 200 MPa injection pressure. The effect of injection pressure on soot-NOx formation is investigated for a variety of boost conditions, representing the conditions of single to multi-stage turbocharger systems. Analysis of the data is performed at the application relevant soot to NOx ratio of approximately 1:10. It is observed that above a critical injection pressure, soot-NOx emissions are not reduced any further.

The introduction of CO₂-reduction technologies like Start-Stop or the Hybrid-Powertrain and the future emission legislation require a detailed optimization of the engine start-up. The combustion concept development as well as the calibration of the ECU makes an explicit thermodynamic analysis of the combustion process during the start-up necessary. Initially, the well-known thermodynamic analysis of in-cylinder pressure at stationary condition was transmitted to the highly non-stationary engine start-up. There, the current models for calculation of the transient wall heat fluxes were found to be misleading. Therefore, adaptations to the start-up conditions of the known models by Woschni, Hohenberg and Bargende were introduced for calculation of the wall heat transfer coefficient in SI engines with gasoline direct injection. This paper shows how the indicated values can be measured during the engine start-up.

Active safety systems will have a great impact in the next generation of vehicles. This is partly originated by the increasing consumer's interest for safety and partly by new traffic safety laws. Control actions in the vehicle are based on an extensive environment model which contains information about relevant objects in vehicle surroundings. Sensor data fusion integrates measurements from different surround sensors into this environment model. In order to avoid system malfunctions, high reliability in the interpretation of the situation, and therefore in the environment model, is essential. Hence, the main idea of data fusion is to make use of the advantages of using multiple sensors and different technologies in order to fulfill these requirements, which are especially high due to autonomous interventions in vehicle dynamics (e. g. automatic emergency braking).

In-cylinder spray imaging by Mie scattering has been taken with frame rates up to 27,000 fps, along with high speed video photography of chemiluminescence and soot thermal radiation. Spectroscopic measurements have confirmed the presence of OH*, CH* and C2* emissions lines, and their magnitude relative compared to soot radiation. Filtering for CH* has been used with both the high speed video and a Photo-Multiplier Tube (PMT). The PMT signals have been found to correlate with the rate of heat release derived from in-cylinder pressure measurements. A high power photographic strobe has been used to illuminate the fuel spray. Images show that the fuel spray can strike the ground strap of the spark plug, break up, and a fuel cloud then drifts over and under the strap through the spark plug gap. Tests have conducted at two different spark plug orientations using a single spark strategy.

Due to the increasingly stricter emission legislation and growing demands for lower fuel consumption, there have been significant efforts to improve combustion efficiency while satisfying the emission requirements. Homogeneous Charge Compression Ignition (HCCI) combined with turbo/supercharging on gasoline engines provides a particularly promising and, at the same time, a challenging approach. Naturally aspirated (n.a.) HCCI has already shown a considerable potential of about 14% in the New European Driving Cycle (NEDC) compared with a conventional 4-cylinder 2.0 liter gasoline Port Fuel Injection (PFI) engine without any advanced valve-train technology. The HCCI n.a. operation range is air breathing limited due to the hot residuals required for the self-ignition and to slow down reaction kinetics, and therefore is limited to a part-load operation area.

Regarding the strongly growing two-wheeler market fuel economy, price and emission legislations are in focus of current development work. Fuel economy as well as emissions can be improved by introduction of engine management systems (EMS). In order to provide the benefits of an EMS for low cost motorcycles, efforts are being made at BOSCH to reduce the costs of a port fuel injection (PFI) system. The present paper describes a method of how to reduce the number of sensors of a PFI system by the use of sophisticated software functions based on high-resolution engine speed evaluation. In order to improve the performance of a system working without a MAP-sensor (manifold air pressure sensor) an air charge feature (ACFn) based on engine speed is introduced. It is shown by an experiment that ACFn allows to detect and adapt changes in manifold air pressure. Cross-influences on ACFn are analyzed by simulations and engine test bench measurements.

In order to comply with more and more stringent emission standards, like EU6 which will be mandatory starting in September 2014, GDI engines have to be further optimized particularly in regard of PN emissions. It is generally accepted that the deposition of liquid fuel wall films in the combustion chamber is a significant source of particulate formation in GDI engines. Particularly the wall surface temperature and the temperature drop due to the interaction with liquid fuel spray were identified as important parameters influencing the spray-wall interaction [1]. In order to quantify this temperature drop at combustion chamber surfaces, surface temperature measurements on the piston of a single-cylinder engine were conducted. Therefore, eight fast-response thermocouples were embedded 0.3 μm beneath the piston surface and the signals were transmitted from the moving piston to the data acquisition system via telemetry.

Due to the principle of direct injection, which is applied in modern homogeneously operated gasoline engines, there are various operation points with significant particulate emissions. The spray droplets contact the piston surface during the warm-up and early injections, in particular. The fuel wall films and the resulting delayed evaporation of the liquid fuel is one of the main sources of soot particles. It is therefore necessary to carry out investigations into the formation of wall film. The influence of the spray impact angle is of special interest, as this is a major difference between engines with side-mounted injectors and centrally positioned injectors. This paper describes an infrared thermography-based method, which we used to carry out a systematic study of fuel deposits on the walls of the combustion chamber. The boundary conditions of the test section were close to those of real GDI engines operated with homogeneous charge.

The spray-guided combustion process offers a high potential for fuel savings in gasoline engines in the part load range. In this connection, the injector and spark plug are arranged in close proximity to one another, as a result of which mixture formation is primarily shaped by the dynamics of the fuel spray. The mixture formation time is very short, so that at the time of ignition the velocity of flow is high and the fuel is still largely present in liquid form. The quality of mixture formation thus constitutes a key aspect of reliable ignition. In this article, the spray characteristics of an outward-opening piezo injector are examined using optical testing methods under pressure chamber conditions and the results obtained are correlated with ignition behaviour in-engine. The global spray formation is examined using high-speed visualisation methods, particularly with regard to cyclical fluctuations.

Equipping low cost two-wheelers with engine management systems (EMS) enables not only a reduction of emissions but also an improvement in fuel consumption and system robustness. These benefits are accompanied by initially higher system costs compared to carburetor systems. Therefore, intelligent software solutions are developed by Bosch, which enable a reduction of the necessary sensors for a port fuel injection system (PFI) and furthermore provide new possibilities for combustion control. One example for these intelligent software solutions is a model based evaluation of the engine speed. By use of the information contained in the engine speed signal, characteristic features like air charge, indicated mean effective pressure (imep) and combustion phasing are derivable. The present paper illustrates how these features could be used to reduce the system costs and to improve fuel consumption and system robustness.

Cost reduction of engine management systems (EMS) for two-wheeler applications is the key to utilize their potentials compared to carburetor bikes regarding emissions, fuel economy and system robustness. In order to reduce the costs of a system with port fuel injection (PFI) Bosch is developing an EMS without a manifold air pressure (MAP) sensor. The pressure sensor is usually used to compensate for different influences on the air mass, which cannot be detected via the throttle position sensor (TPS) and mean engine speed. Such influences are different leakage rates of the throttle body and changing ambient conditions like air pressure. Bosch has shown in the past that a virtual sensor relying on model based evaluation of engine speed can be used for a detection of leakage air mass in idling to improve the pre-control of the air-fuel ratio. This provides a functionality which so far was only possible with an intake pressure sensor.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

India contributed to 11% of the global road accidents and was ranked 1st among road deaths according to the latest World Health Organization (WHO) report 2018. Indian National Highways (NH) is a meagre 5% of the country’s road network but accounts for 55% of the road accidents and 61% of the road deaths. Majority of the freight traffic is ferried by Commercial Vehicles (CV) or trucks along these highways and this in turn increases the probability of them being involved in a road accident. The country’s economy is forecasted to thrive in the coming years and hence the requirement of CVs is aligned to international categorisation in the supply chain and shall play a pivotal role. In the year 2019, 13,532 road deaths were associated with CV occupants. The trucking industry is an unorganized sector wherein the illegal overloading of vehicles and over-the-limit driving hours pose a serious threat to road users.

The fuel-independent particulate emissions of a direct injection gasoline engine were investigated. This was done by running the engine with reference gasoline at four different loads and then switching to hydrogen or methane port fuel operation and comparing the resulting particulate emissions and their size distribution. Differences in the combustion characteristics of hydrogen and gasoline were accounted for by diluting the inlet air with nitrogen and matching the pressure or heat release traces to those of gasoline operation. Methane operation is expected to generate particulate emissions lower by several orders of magnitude compared to gasoline and hydrogen does not contribute to carbon soot formation because of the lack of carbon atoms in the molecule. Thus, any remaining particulate emissions at hydrogen gas operation must arise from non fuel related sources, e.g. from lubrication oil, metal abrasion or inlet air.

The introduction of transient test cycles and the focus on real world driving emissions has increased the importance of ensuring the NOx and soot emissions are controlled during transient manoeuvres. At the same time, there is a drive to reduce the number of calibration variables used by engine control strategies to reduce development effort and costs. In this paper, a control orientated combustion model, [1], and model predictive control strategy, [2], that were developed in simulation and reported in earlier papers, are applied to a Diesel engine and demonstrated in a test vehicle. The paper describes how the control approach developed in simulation was implemented in embedded hardware, using an FPGA to accelerate the emissions calculations. The development of the predictive controller includes the application of a simplified optimisation algorithm to enable a real-time calculation in the test vehicle.

In-cylinder temperature measurements are vital for the validation of gasoline engine modelling and useful in their own right for explaining differences in engine performance. The underlying chemical reactions in combustion are highly sensitive to temperature and affect emissions of both NOx and particulate matter. The two techniques described here are complementary, and can be used for insights into the quality of mixture preparation by measurement of the in-cylinder temperature distribution during the compression stroke. The influence of fuel composition on in-cylinder mixture temperatures can also be resolved. Laser Induced Grating Spectroscopy (LIGS) provides point temperature measurements with a pressure dependent precision in the range 0.1 to 1.0 % when the gas composition is well characterized and homogeneous; as the pressure increases the precision improves.

In this study, the role of turbulence-chemistry interaction in diesel spray auto-ignition, flame stabilization and end of injection phenomena is investigated under engine relevant “Spray A” conditions. A recently developed diesel spray combustion modeling approach, Conditional Source-term Estimation (CSE-FGM), is coupled with Reynolds-averaged Navier-Stokes simulation (RANS) framework to study the details of spray combustion. The detailed chemistry mechanism is included through the Flamelet Generated Manifold (FGM) method. Both unsteady and steady flamelet solutions are included in the manifold to account for the auto-ignition process and the subsequent flame propagation in a diesel spray. Conditionally averaged chemical source terms are closed by the conditional scalars obtained in the CSE routine. Both non-reacting and reacting spray jets are computed over a wide range of Engine Combustion Network (ECN) diesel. “Spray A” conditions.

This study looked into the application of active thermal coatings on the surfaces of the combustion chamber as a method of improving the thermal efficiency of internal combustion engines. The active thermal coating was applied to a production aluminium piston and its performance was compared against a reference aluminium piston on a single-cylinder diesel engine. The two pistons were tested over a wide range of speed/load conditions and the effects of EGR and combustion phasing on engine performance and tailpipe emissions were also investigated. A detailed energy balance approach was employed to study the thermal behaviour of the active thermal coating. In general, improvements in indicated specific fuel consumption were not statistically significant for the coated piston over the whole test matrix. Mean exhaust temperature showed a marginal increase with the coated piston of up to 6 °C.

Fully Variable Valve Actuation (FVVA) systems enable to employ a wide range of combustion strategies by providing the actuation of a gas exchange valve at an arbitrary point in time, with variable lift and adjustable ramps for opening and closing. Making such a system ready for the market requires appropriate fault-diagnostic functionality. Here, we focus on diagnosis possibilities by using air intake system sensors such as Manifold Absolute Pressure (MAP) sensors. Results obtained on a 4-cylinder test bench engine are presented for the early intake opening strategy under different loads, and at medium range rotational speeds on steady-state conditions. It is shown that detection and identification of the different critical faults on each actuator is possible by using a Fourier series signal model of the MAP sensor.

Advanced engine control and diagnosis strategies for internal combustion engines need accurate feedback information from the combustion engine. The feedback information can be utilized to control combustion features which allow the improvement of engine's efficiency through real-time control and diagnosis of the combustion process. This article describes a new method for combustion phase and IMEP estimation using one in-cylinder pressure and engine speed. In order to take torsional deflections of the crankshaft into account a gray-box model of the crankshaft is identified by subspace identification. The modeling accuracy is compared to a stiff physical crankshaft model. For combustion feature estimation, the identified MISO (multiple input single output) system is inverted. Experiments for a four-cylinder spark-ignition engine show the superior performance of the new method for combustion feature estimation compared to a stiff model approach.